I was recently asked to give a few tips for data collection and analysis, so without much ado, here is what I’ve been recommending:
- Keep a log: Use a labbook or other form of log of your preparation, experiments, and thoughts along the way. You won’t remember later on what you did.
- Link your research question to your setup and tools: Regardless of your field, you have to make sure that your methods and research question are fully aligned. It may be tempting to add more and more things to your methods – to add more questions to your questionnaire, or to stick just more and more sensors on your specimen. At the end of the day, you may get overwhelmed by all the data.
- Script data-processing: Program as much as possible of your data post-processing. Nobody wants to be handling a massive Excel sheet – code is much cleaner to work with.
- Analyze wisely: Again, think about your research question when you analyze your data. You can keep carrying out additional calculations and modifications to your data, but it will just create more noise.
- Keep a log: I know I already said this – but also keep a log of your analysis: which changes did you make to your code on a particular day? Which insights did you have a long the way?
These are some of my quick tips for data collection and analysis! What has helped you most in data collection and analysis?